Triple
T1810023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agelastes |
E40309
|
entity |
| Predicate | vernacularGrouping |
P32163
|
FINISHED |
| Object | guineafowl |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: guineafowl | Statement: [Agelastes, vernacularGrouping, guineafowl]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vernacularGrouping Context triple: [Agelastes, vernacularGrouping, guineafowl]
-
A.
regionalGrouping
Indicates that entities are organized or associated together based on shared geographic or regional characteristics.
-
B.
macrolanguageGrouping
Indicates that one language is classified as part of a broader macrolanguage grouping that encompasses multiple closely related language varieties.
-
C.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
D.
localeType
Indicates the classification or category of a locale (such as region, city, or venue type) that characterizes the kind of place involved in the relationship.
-
E.
majorLanguageGroupOf
Indicates that one language group is the primary or dominant linguistic classification to which another language or set of languages belongs.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab694d75ac8190a4d61399c04b9fb9 |
completed | March 6, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69aa61d6b8ec8190a1597b2e44ea6534 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab694bf6a08190a02ce2fc979e6701 |
completed | March 6, 2026, 11:54 p.m. |
Created at: March 4, 2026, 7:32 p.m.